System for spectral shaping of vehicle noise cancellation

ABSTRACT

The present disclosure is directed to a system and a method for spectral shaping of vehicle noise cancellation. In an example implementation, the method includes determining a center frequency of an expected tonal peak within a selected noise band based upon vehicle data, generating a noise cancellation signal using a weighted shaping filter to shape the noise band, and outputting the noise cancellation signal to smooth the expected tonal peak.

INTRODUCTION

The information provided in this section is for the purpose of generallypresenting the context of the disclosure. Work of the presently namedinventors, to the extent it is described in this section, as well asaspects of the description that may not otherwise qualify as prior artat the time of filing, are neither expressly nor impliedly admitted asprior art against the present disclosure.

The present disclosure relates to shaping vehicle noise, and moreparticularly to a system and method to shape tonal noises by way ofnoise cancellation signals.

During operation, drivers and passengers experience noises that may beundesirable. For example, vehicles are subject to road noise caused bydefects in the road. In other examples, vehicles generate known noises,or tones, at expected frequencies based upon the vehicle attributes,such as tire size, tire cavity, and/or speed of the vehicle.

SUMMARY

In an example, a vehicle noise shaping system is disclosed. In anexample implementation, the vehicle noise shaping system includes atonal noise monitoring module that determines a center frequency of anexpected tonal peak within a selected noise band based upon vehicle dataand determines whether (1) a difference between a decibel value of theexpected tonal peak within the selected noise band and a root meansquare value of the selected noise band or (2) a ratio between thedecibel value of the expected tonal peak within the selected noise bandand the root mean square value of the selected noise band exceeds apredetermined threshold. The vehicle noise shaping system also includesa noise shaping module that uses a weighted shaping filter to generate anoise cancellation signal when the difference or the ratio exceeds thepredetermined threshold to shape the noise band. The vehicle noiseshaping system also includes an audio output module that is configuredto output the noise cancellation signal to smooth the expected tonalpeak when the difference or the ratio exceeds the predeterminedthreshold.

In other features, the vehicle noise shaping system the vehicle noiseshaping system also includes an attribute adjustment module thatdetermines whether the tonal peak is within a predetermined frequencyrange when the difference or the ratio does not exceed the predeterminedthreshold and adjusts a vehicle attribute when the tonal peak is withinthe predetermined frequency range.

In other features, the tonal noise monitoring module calculates thedifference between the decibel value of the expected tonal peak and theroot mean square value of the selected noise band or the ratio of thedecibel value of the expected tonal peak and the root mean square valueof the selected noise band.

In other features, the audio output module outputs the noisecancellation signal to one or more speakers when the difference or theratio exceeds the predetermined threshold. In other features, the tonalnoise monitoring module receives the vehicle data from one or morevehicle sensors. In other features, the tonal noise monitoring moduleselects the center frequency of the expected tonal peak based upon thevehicle data. In other features, the vehicle data represents a speed ofa vehicle, a temperature associated with the vehicle, or a vibrationassociated with the vehicle. In other features, the noise shaping moduleselects filtering weights according to the difference or the ratio toshape the noise cancellation signal according to the selected filteringweights. In other features, the weighted shaping filter comprises abandpass filter, a bandstop filter, a high-pass filter, or a low-passfilter.

In an example, a system is disclosed. The system includes an activenoise cancellation module that receives a signal indicative ofenvironmental noise within a vehicle cabin and generates a noisecancellation signal based upon the signal. The system also includes atonal noise cancellation module in communication with the active noisecancellation module. The tonal noise cancellation module includes atonal noise monitoring module that is configured to determine a centerfrequency of a tonal peak within a selected noise band based upon thesignal and a noise shaping module that uses a weighted shaping filter togenerate a noise cancellation signal to shape the noise band. The tonalnoise cancellation module also includes an audio output module thatoutputs the noise cancellation signal to smooth the tonal peak.

In other features, the audio output module outputs the noisecancellation signal to one or more speakers disposed within a vehiclecabin.

In an example, a method is disclosed. The method includes determining acenter frequency of an expected tonal peak within a selected noise bandbased upon vehicle data, generating a noise cancellation signal using aweighted shaping filter to shape the noise band, and outputting thenoise cancellation signal to smooth the expected tonal peak.

In other features, the method also includes determining whether (1) adifference between a decibel value of the expected tonal peak within theselected noise band and a root mean square value of the selected noiseband or (2) a ratio between the decibel value of the expected tonal peakwithin the selected noise band and the root mean square value of theselected noise band exceeds a predetermined threshold, generating thenoise cancellation signal using the weighted shaping filter when thedifference or the ratio exceeds the predetermined threshold, andoutputting the noise cancellation signal to smooth the expected tonalpeak when the difference or the ratio exceeds the predeterminedthreshold.

In other features, the method includes calculating the differencebetween the decibel value of the expected tonal peak and the root meansquare value of the selected noise band or the ratio of the decibelvalue of the expected tonal peak and the root mean square value of theselected noise band. In other features, the method includes outputtingthe noise cancellation signal to one or more speakers when thedifference or the ratio exceeds the predetermined threshold.

In other features, the method includes receiving the vehicle data fromone or more vehicle sensors. In other features, the method includesselecting the center frequency of the expected tonal peak based upon thevehicle data. In other features, the vehicle data represents a speed ofa vehicle, a temperature associated with the vehicle, or a vibrationassociated with the vehicle. In other features, the method includesselecting filtering weights according to the difference or the ratio toshape the noise cancellation signal according to the selected filteringweights. In other features, the weighted shaping filter comprises atleast one of a bandpass filter, a bandstop filter, a high-pass filter,and a low-pass filter

Further areas of applicability of the present disclosure will becomeapparent from the detailed description, the claims and the drawings. Thedetailed description and specific examples are intended for purposes ofillustration only and are not intended to limit the scope of thedisclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure will become more fully understood from thedetailed description and the accompanying drawings, wherein:

FIG. 1 is diagrammatic illustration of a vehicle including a vehiclenoise shaping system in accordance with an example implementation of thepresent disclosure;

FIG. 2A is block diagram illustrating the vehicle noise shaping systemin accordance with an example implementation of the present disclosure;

FIG. 2B is another block diagram illustrating the vehicle noise shapingsystem, where the vehicle shaping system includes a noise cancellationmodule and a tonal noise cancellation module in accordance with anexample implementation of the present disclosure;

FIG. 3A is a graph illustrating a measured unaltered noise signal and ameasured noise signal modified by active noise cancellation systems;

FIG. 3B is a graph illustrating an example noise cancellation signal toreduce the measured unaltered noise of FIG. 3A in accordance with anexample implementation of the present disclosure;

FIG. 3C is a graph illustrating the measured unaltered noise signal andthe measured noise signal modified by a noise cancellation system inaccordance with an example implementation of the present disclosure;

FIG. 3D is a graph is a graph illustrating an example noise cancellationsignal generated by the noise cancellation system to reduce the measuredunaltered noise of FIG. 3C, where the noise cancellation system uses ashaping filter to generate noise cancellation signals that smooth tonalpeaks in accordance with an example implementation of the presentdisclosure; and

FIG. 4 is a flow diagram illustrating an example method for monitoringtonal noise according to an example implementation of the presentdisclosure.

In the drawings, reference numbers may be reused to identify similarand/or identical elements.

DETAILED DESCRIPTION

A system and method according to the present disclosure shapes tonalnoise by applying weighting filters to the cancellation output signal inorder to modify the overall perception of the tonal noises naturallypresent within the vehicle. Current noise cancellation systems, such asactive noise cancellation systems (i.e., road noise cancellationsystems) provide reduction in broad band noise by reducing the noisesignal over the frequency band. However, these noise cancellationsystems may not reduce tonal peaks to the broad band noise floor. Thus,an occupant of the vehicle may still experience these tonal peaks evenafter the noise signal was reduced. The system and method describedherein may improve the overall perceptibility of the tonal peaks byapplying a shaping filter to the tonal peak portion of the cancellationsignal (i.e., noise cancellation signal). For example, the system andmethod can shape the peak portion to reduce the decibel levelexperienced by the occupants as compared to other vehicle noisecancellation systems.

The system and method can include a tonal noise monitoring module thatdetermines a center frequency of an expected tonal peak within aselected noise band based upon vehicle data and determines whether adifference between a decibel value of the expected tonal peak and a rootmean square value of the selected noise band or a ratio between thedecibel value of the expected tonal peak and the root mean square valueof the selected noise band exceeds the predetermined threshold. Thesystem and method can also include a noise shaping module that applies ashaping filter to a noise band including the tonal peak when thedifference exceeds the predetermined threshold to shape the noise band.The system and method also includes an audio output module that outputsthe filtered noise band when the tone exceeds the predeterminedparameter.

FIG. 1 illustrates a vehicle environment 100 in accordance with anexample implementation of the present disclosure. The vehicleenvironment 100 includes a vehicle 102. As shown, the vehicle 102includes one or more microphones 104 and one or more speakers 106. Themicrophones 104 detect sound within the vehicle 102 cabin. The speakers106 generate various sounds within the vehicle 102 and/or outside of thevehicle 102. For example, the speakers 106 emit sound waves havingapproximately the same amplitude but with an inverted phase (i.e.,antiphase) to at least partially cancel the noise detected by themicrophones. The microphones 104 can be deployed throughout the vehicle102 to capture sound that occupants can hear. The speakers 106 may bedeployed throughout the interior, such as in the doors, the rear shelf,and/or the roof, of the vehicle 102 to cancel noise detected by themicrophones 104.

In an example, a roadway 108 traveled by vehicles, such as the vehicle102, may include roadway defects 110, such as damaged asphalt and thelike. While traveling the roadway 108, the vehicle 102 may encounter theroadway defects 110, which can result in undesired noise detectable bythe microphones 104. As described in greater detail herein, the speakers106 can generate audio that reduces the perceptibility of the undesiredsound to the drivers and/or passengers of the vehicle 102.

The vehicle 102 includes one or more sensors that measure vehicle data.For example, the vehicle 102 can include a wheel speed sensor 112mounted to one or more wheels of the vehicle 102 and measures the speedof the wheels. The vehicle 102 can also include a temperature sensor 114that measures a temperature. For example, the temperature sensor canmeasure a temperature of one or more tires of the vehicle 102, anambient temperature, and/or an engine temperature. The vehicle 102 canalso include a vibrational sensor 115 that is configured to measure oneor more vibrations corresponding to the vehicle 102. For example, thevibrational sensor 115 can measure vibrations experienced by the vehicle102 when the vehicle 102 travels over a roadway 108 including roadwaydefects 110.

The vehicle 102 includes a noise cancellation module 116. The noisecancellation module 116 may include an active noise cancellation systemthat generates signals having approximately the same amplitude asdetected noise but having an inverted phase with respect to the detectednoise signals. In an implementation, the microphones 104 detect noiseand provide data representing the noise to the noise cancellation module116. The noise cancellation module 116 processes the data and generatesa signal that is emitted at the speakers 106 that effectively cancels(i.e., through destructive interference) the noise perceptible withinthe vehicle 102. For example, the microphones 104 can detect road noisegenerated by the vehicle 102 traveling over the roadway defects 110, andthe noise cancellation module 116 generates sound that effectivelycancels the road noise.

Referring to FIG. 2A, the noise cancellation module 116 includes a tonalnoise cancellation module 200. Tonal noises are wave forms that occur ata single frequency. For example, tonal noises occur at predictablefrequencies based upon the vehicle operating environment, such asrotational speeds of drive shafts, number of pistons, speed of thevehicle, tire size, tire cavity size, other mechanical noise sources,and/or audio output. Active noise cancellation systems, such as thenoise cancellation module 116, can reduce the overall noise perceptibleto occupants of the vehicle 102. However, tonal peaks may still resultin undesirable experiences due to the sharp peak perceptible to theoccupants.

FIG. 2B illustrates another example implementation of the vehicle noisecancellation system disclosed herein. The noise cancellation module 116can operate during operation of the vehicle 102. Upon determining thatan expected tonal peak is forthcoming, the tonal noise cancellationmodule 200 initiates operation to generate a noise cancellation signalto shape the tonal peak noise as described herein. Upon determining thevehicle data has been modified or that the tonal peak cannot beidentified, the noise cancellation module 116 initiates operation.

As described in greater detail herein, the tonal noise cancellationmodule 200 initiates operation based upon the tracked vehicle data. Forexample, the tonal noise cancellation module 200, using the trackedvehicle data, can determine that a tonal peak is expected at a definedfrequency and generate a weighted signal that interferes with the tonalpeak at the center frequency of the tonal peak.

The tonal noise cancellation module 200 monitors vehicle data measuredby the various sensors, such as the wheel speed sensor 112 and/or thetemperature sensor 114. The tonal noise cancellation module 200 alsomonitors noise detected by the microphones 104. As shown in FIG. 2A, thetonal noise cancellation module 200 includes a tonal noise monitoringmodule 202, a noise shaping module 204, an attribute adjustment module206, memory 208, and an audio output module 210.

The tonal noise monitoring module 202 monitors vehicle data and/or noisedata. During operation, the tonal noise monitoring module 202 caninitiate operation of the tonal noise cancellation module 200 based uponthe monitored vehicle data and/or monitored noise. In an implementation,the tonal noise monitoring module 202 receives vehicle data representingvehicle parameters, such as current speed, temperature, vibration, andthe like, from the sensors 112, 114, 115 and/or data indicative ofmeasured sound from the microphones 104. The tonal noise monitoringmodule 202 determines a tonal noise band to monitor based upon themonitored vehicle data. For example, the memory 208 stores expectedtonal noise profiles corresponding to various vehicle attributes (i.e.,tire size, tire cavity size, engine components, speed, temperature,etc.) and the monitored vehicle data.

The expected tonal noise profiles represent expected tonal peaks withina defined frequency band (i.e., tonal noise band) based upon the vehicleattributes and monitored vehicle data. The expected tonal noise profilemay include a look-up table indicating expected tonal peak at a centerfrequency based upon the vehicle attributes and monitored vehicle data.Thus, the tonal noise monitoring module 202 can initiate a look-upoperation based upon the monitored vehicle data to obtain weights forgenerating an interference signal corresponding to the tonal peak. Thetonal noise profile may be pre-populated based upon the vehicleattributes or updated if the vehicle attributes have changed.

For example, a vehicle 102 having a specific speed parameter and/orspecific temperature parameter corresponds to an expected tonal peak ata center frequency. If the monitored vehicle data corresponds to thepredetermined vehicle attributes, the tonal noise band including theexpected center frequency is selected for monitoring. The selected tonalnoise band can include a lower tonal noise band limit (i.e., a lowerfrequency) and an upper tonal noise band limit (i.e., an upperfrequency) within a predetermined range of the expected centerfrequency.

The tonal noise monitoring module 202 monitors the noise data receivedfrom at microphones 104 within the selected tonal noise band. In animplementation, the tonal noise monitoring module 202 identifies theexpected center frequency within the tonal noise band and calculates adifference between a decibel (dB) value of the tonal noise at theexpected center frequency (i.e., expected tonal peak) and a root meansquare (RMS) of the tonal noise band. The tonal noise monitoring module202 then determines whether the difference exceeds a predeterminedthreshold. Additionally, the tonal noise monitoring module 202 cancalculate a ratio between the decibel (dB) value of the tonal noise atthe expected center frequency (i.e., expected tonal peak) and the rootmean square (RMS) of the tonal noise band.

The noise shaping module 204 initiates shaping filter to generateinterference noise focused at the tonal peak to shape the tonal peakwhen the difference and/or the radio exceeds the predeterminedthreshold. The shaping filter generates interference noise according toone or more weights to generate a desired noise signal that smoothes thetonal peak as compared to active noise cancellation systems.

For example and as discussed below in reference to FIGS. 3A through 3D,the spectral content of a noise signal at and around the tonal peak maybe reduced as compared to the tonal speak reduced by other noisecancellation systems, and the spectral content of other portions (i.e.,side bands) of the noise signals may be higher as compared to the noisesignal reduced by the other noise cancellation systems.

FIG. 3A illustrates a graph 300 according to an example implementationof the present disclosure. The graph 300 includes an unaltered noisesignal 302 measured over a frequency band. The graph 300 also includes anoise signal 304 altered by active cancellation systems, including roadnoise cancellation systems. Active noise cancellation system attempt toreduce the spectral content of the noise signal 302 across the wholefrequency band by generating the interference noise. The signals 302,304 includes a respective expected tonal peak 306, 308 occurring atabout two hundred and thirty Hertz (230 Hz). FIG. 3B illustrates a graph320 illustrating a portion of example interference noise signal 322generated by an active noise cancellation system (i.e., the noisecancellation module 116).

FIG. 3C illustrates a graph 330 the unaltered noise signal 302 measuredover the frequency band and a noise signal 332 alerted by theinterference noise signal (see FIG. 3D) generated by the noise shapingmodule 204. As shown, the unaltered noise signal 302 includes a tonalpeak 306. The tonal noise determination module 202 determines the centerfrequency corresponding to the tonal peak 306 and the correspondingtonal noise band 334 to monitor. In this example, the tonal noise band334 to monitor ranges from about approximately one hundred and seventyHertz (170 Hz) (i.e., lower tonal noise band limit) and approximatelytwo hundred and seventy Hertz (270 Hz).

The noise shaping module 204 generates the interference signal to shapethe corresponding portions of the noise signal 332. As shown, the shapedportion 336 of the noise signal 332 corresponding to the expected tonalpeak 306 is smoothed with respect to tonal peak 308 shown in FIG. 3A.However the side band portions 338, 339 of the noise signal 332 have ahigher decibel measurement with respect to the corresponding portions ofthe noise signal 304. FIG. 3D is a graph 340 illustrating an exampleinterference signal 342 generated by the noise cancellation module 116and the tonal noise cancellation module 200 to interfere with the noisesignal 302.

For example, the noise shaping module 204 accesses the memory 208 toobtain corresponding weights to the tonal peak based upon the tonalnoise profile. In this example, the noise shaping module 204 applies theweights to shaping filter to generate interference noise aboutfrequencies corresponding to the tonal noise band 334. The energy of theinterference noise may be higher around the center frequency (i.e.,+/−twenty Hertz (20 Hz)) to shape (i.e., smooth) the tonal peak 306 tothe shaped portion 336.

As shown in FIGS. 3B and 3D, the energy of the interference signalaround two hundred and thirty Hertz (230 Hz), which is the centerfrequency of the expected tonal peak, is greater in the interferencenoise signal 342 as compared to the interference noise signal 322.Additionally, as illustrated in FIGS. 3B and 3D, the energycorresponding to the side bands 338, 339 of the interference signal aregenerally higher in the interference noise signal 322 as compared to theinterference noise signal 342. The interference noise signal 342 shapesthe tonal noise band 334 portion of the noise signal 332 to reduceoccupant perceptibility of the tonal noise peak. Thus, the weightedshaping filter may cause noise shaping module to generate noisecancellation signals having higher energy at frequencies correspondingto tonal peaks and lower energy at frequencies corresponding to the sidebands to shape the noise signals.

The shaping filter may include any number of filters, such as digitalfilters, that is used to generate noise cancellation signals (i.e.,signals that are out of phase with the detected noise signals). Forexample, the shaping filters may be bandpass filters, bandstop filters,low-pass filters, high-pass filters, or the like, configured to generateinterference noise signals.

Referring back to FIG. 2A, once the noise cancellation signal isgenerated by the noise shaping module 204, the audio output module 210outputs the noise cancellation signal. For example, the audio outputmodule 210 outputs the noise cancellation signal to the speakers 106 toreduce the perceptibility of the noise.

The attribute adjustment module 206 can adjust the vehicle 102attributes when the difference does not exceed the predeterminedthreshold. For example, the attribute adjustment module 206 determineswhether the tonal peak is identified within a predetermined range (i.e.,ten Hertz (10 Hz), twenty Hertz (20 Hz), etc.) of the center frequency.If the attribute adjustment module 206 determines the tonal peak iswithin the predetermined range, the attribute adjustment module 206adjusts one or more vehicle attributes.

For example, based upon the deviation from the expected frequency, theattribute adjustment module 206 can access the memory 208 to retrieve aneffective tire size and/or tire cavity corresponding to the deviation.In another example, the attribute adjustment module 206 requests theoperator/owner of the vehicle 102 to input the vehicle attributes at auser interface 212. The user interface 212 may be any suitable userinterface, such as a touch panel within the vehicle or a mobileelectronic device in communication with the vehicle 102. In yet anotherexample, the attribute adjustment module 206 calculates the vehicleattributes, such as the effective tire size and/or tire cavity size. Theattribute adjustment module 206 can retrieve a calculation functionstored in the memory 208 to calculate the vehicle attributes based uponthe deviation. The updated vehicle attributes can be updated in thememory 208 for monitoring purposes.

FIG. 4 illustrates an example method 400 for monitoring tonal noiseassociated with the vehicle 102. The method 400 is described in thecontext of the modules included in the example implementation of thenoise cancellation module 116 shown in FIG. 2A. However, the particularmodules that perform the steps of the method may be different than thosementioned below and/or the method may be implemented apart from themodules of FIG. 2A.

The method 400 begins at 402. In some implementations, the noisecancellation module 116 is operational and generating noise cancellationsignals according to active noise cancellation protocols. At 404,vehicle data is received at the tonal noise monitoring module 202. Thevehicle data can include monitored vehicle data including speed,temperature, or the like. At 406, the tonal noise monitoring module 202selects the expected center frequency of the tonal noise peak based uponthe monitored vehicle data and corresponding vehicle attributes. At 408,the tonal noise monitoring module 202 monitors noise data within thetonal noise band. At 410, the tonal noise monitoring module 202determines whether the difference and/or the ratio between the decibelvalue corresponding to the center frequency of the expected tonal peakand the root mean square value of the monitored tonal noise band isgreater than the predetermined threshold. In implementations, the tonalnoise monitoring module 202 calculates the difference and/or the radioand then determines whether the difference and/or the ratio exceedpredetermined thresholds.

The noise shaping module 204 initiates spectral shaping of a noisecancellation signal when the difference is greater than thepredetermined threshold at 412. At 414, the noise shaping module 204retrieves the filter weights from the memory 208 based upon the tonalnoise band. At 416, the noise shaping module 204 generates the noisecancellation signal using the shaping filter. At 418, the audio outputmodule 210 outputs the noise cancellation signal at the speakers 106.

At 420, the noise shaping module 204 determines whether the vehicle datahas changed (i.e., change in speed, change in temperature) or whetherthe difference is below the predetermined threshold. If vehicle data haschanged, the method 400 returns to 406 to identify other potentialexpected tonal noised based upon the updated vehicle data. If thedifference is below the predetermined threshold, the method 400 ends at422. For instance, the noise cancellation module 116 may initiate activenoise cancellation protocols.

If the difference is below the predetermined threshold at 410, theattribute adjustment module 206 determines whether the tonal peak iswithin a predetermined range of the expected center frequency at 424. Ifthe tonal peak is within the predetermined range, the attributeadjustment module 206 determines the updated vehicle attributes at 426and stores in the memory 208. If the tonal peak is not within thepredetermined range, the method 400 ends at 422.

The foregoing description is merely illustrative in nature and is in noway intended to limit the disclosure, its application, or uses. Thebroad teachings of the disclosure can be implemented in a variety offorms. Therefore, while this disclosure includes particular examples,the true scope of the disclosure should not be so limited since othermodifications will become apparent upon a study of the drawings, thespecification, and the following claims. It should be understood thatone or more steps within a method may be executed in different order (orconcurrently) without altering the principles of the present disclosure.Further, although each of the embodiments is described above as havingcertain features, any one or more of those features described withrespect to any embodiment of the disclosure can be implemented in and/orcombined with features of any of the other embodiments, even if thatcombination is not explicitly described. In other words, the describedembodiments are not mutually exclusive, and permutations of one or moreembodiments with one another remain within the scope of this disclosure.

Spatial and functional relationships between elements (for example,between modules, circuit elements, semiconductor layers, etc.) aredescribed using various terms, including “connected,” “engaged,”“coupled,” “adjacent,” “next to,” “on top of,” “above,” “below,” and“disposed.” Unless explicitly described as being “direct,” when arelationship between first and second elements is described in the abovedisclosure, that relationship can be a direct relationship where noother intervening elements are present between the first and secondelements, but can also be an indirect relationship where one or moreintervening elements are present (either spatially or functionally)between the first and second elements. As used herein, the phrase atleast one of A, B, and C should be construed to mean a logical (A OR BOR C), using a non-exclusive logical OR, and should not be construed tomean “at least one of A, at least one of B, and at least one of C.”

In the figures, the direction of an arrow, as indicated by thearrowhead, generally demonstrates the flow of information (such as dataor instructions) that is of interest to the illustration. For example,when element A and element B exchange a variety of information butinformation transmitted from element A to element B is relevant to theillustration, the arrow may point from element A to element B. Thisunidirectional arrow does not imply that no other information istransmitted from element B to element A. Further, for information sentfrom element A to element B, element B may send requests for, or receiptacknowledgements of, the information to element A.

In this application, including the definitions below, the term “module”or the term “controller” may be replaced with the term “circuit.” Theterm “module” may refer to, be part of, or include: an ApplicationSpecific Integrated Circuit (ASIC); a digital, analog, or mixedanalog/digital discrete circuit; a digital, analog, or mixedanalog/digital integrated circuit; a combinational logic circuit; afield programmable gate array (FPGA); a processor circuit (shared,dedicated, or group) that executes code; a memory circuit (shared,dedicated, or group) that stores code executed by the processor circuit;other suitable hardware components that provide the describedfunctionality; or a combination of some or all of the above, such as ina system-on-chip.

The module may include one or more interface circuits. In some examples,the interface circuits may include wired or wireless interfaces that areconnected to a local area network (LAN), the Internet, a wide areanetwork (WAN), or combinations thereof. The functionality of any givenmodule of the present disclosure may be distributed among multiplemodules that are connected via interface circuits. For example, multiplemodules may allow load balancing. In a further example, a server (alsoknown as remote, or cloud) module may accomplish some functionality onbehalf of a client module.

The term code, as used above, may include software, firmware, and/ormicrocode, and may refer to programs, routines, functions, classes, datastructures, and/or objects. The term shared processor circuitencompasses a single processor circuit that executes some or all codefrom multiple modules. The term group processor circuit encompasses aprocessor circuit that, in combination with additional processorcircuits, executes some or all code from one or more modules. Referencesto multiple processor circuits encompass multiple processor circuits ondiscrete dies, multiple processor circuits on a single die, multiplecores of a single processor circuit, multiple threads of a singleprocessor circuit, or a combination of the above. The term shared memorycircuit encompasses a single memory circuit that stores some or all codefrom multiple modules. The term group memory circuit encompasses amemory circuit that, in combination with additional memories, storessome or all code from one or more modules.

The term memory circuit is a subset of the term computer-readablemedium. The term computer-readable medium, as used herein, does notencompass transitory electrical or electromagnetic signals propagatingthrough a medium (such as on a carrier wave); the term computer-readablemedium may therefore be considered tangible and non-transitory.Non-limiting examples of a non-transitory, tangible computer-readablemedium are nonvolatile memory circuits (such as a flash memory circuit,an erasable programmable read-only memory circuit, or a mask read-onlymemory circuit), volatile memory circuits (such as a static randomaccess memory circuit or a dynamic random access memory circuit),magnetic storage media (such as an analog or digital magnetic tape or ahard disk drive), and optical storage media (such as a CD, a DVD, or aBlu-ray Disc).

The apparatuses and methods described in this application may bepartially or fully implemented by a special purpose computer created byconfiguring a general purpose computer to execute one or more particularfunctions embodied in computer programs. The functional blocks,flowchart components, and other elements described above serve assoftware specifications, which can be translated into the computerprograms by the routine work of a skilled technician or programmer.

The computer programs include processor-executable instructions that arestored on at least one non-transitory, tangible computer-readablemedium. The computer programs may also include or rely on stored data.The computer programs may encompass a basic input/output system (BIOS)that interacts with hardware of the special purpose computer, devicedrivers that interact with particular devices of the special purposecomputer, one or more operating systems, user applications, backgroundservices, background applications, etc.

The computer programs may include: (i) descriptive text to be parsed,such as HTML (hypertext markup language), XML (extensible markuplanguage), or JSON (JavaScript Object Notation) (ii) assembly code,(iii) object code generated from source code by a compiler, (iv) sourcecode for execution by an interpreter, (v) source code for compilationand execution by a just-in-time compiler, etc. As examples only, sourcecode may be written using syntax from languages including C, C++, C#,Objective-C, Swift, Haskell, Go, SQL, R, Lisp, Java®, Fortran, Perl,Pascal, Curl, OCaml, Javascript®, HTML5 (Hypertext Markup Language 5threvision), Ada, ASP (Active Server Pages), PHP (PHP: HypertextPreprocessor), Scala, Eiffel, Smalltalk, Erlang, Ruby, Flash®, VisualBasic®, Lua, MATLAB, SIMULINK, and Python®.

None of the elements recited in the claims are intended to be ameans-plus-function element within the meaning of 35 U.S.C. § 112(f)unless an element is expressly recited using the phrase “means for,” orin the case of a method claim using the phrases “operation for” or “stepfor.”

What is claimed is:
 1. A vehicle noise shaping system, comprising: atonal noise monitoring module that is configured to: determine a centerfrequency of an expected tonal peak within a selected noise band basedupon vehicle data, and determine whether at least one of (1) adifference between a decibel value of the expected tonal peak within theselected noise band and a root mean square value of the selected noiseband and (2) a ratio between the decibel value of the expected tonalpeak within the selected noise band and the root mean square value ofthe selected noise band exceeds a predetermined threshold; a noiseshaping module that is configured to use a weighted shaping filter togenerate a noise cancellation signal when at the least one of thedifference and the ratio exceeds the predetermined threshold to shapethe noise band; and an audio output module that is configured to outputthe noise cancellation signal to smooth the expected tonal peak when theat least one of the difference and the ratio exceeds the predeterminedthreshold.
 2. The vehicle noise shaping system as recited in claim 1,further comprising: an attribute adjustment module that is configuredto: determine whether the tonal peak is within a predetermined frequencyrange when at least one of the difference and the ratio is less than orequal to the predetermined threshold, and adjust a vehicle attributewhen the tonal peak is within the predetermined frequency range.
 3. Thevehicle noise shaping system as recited in claim 1, wherein the tonalnoise monitoring module is further configured to calculate at least oneof the difference between the decibel value of the expected tonal peakand the root mean square value of the selected noise band and the ratioof the decibel value of the expected tonal peak and the root mean squarevalue of the selected noise band.
 4. The vehicle noise shaping system asrecited in claim 1, wherein the audio output module is furtherconfigured to output the noise cancellation signal to one or morespeakers when the at least one of the difference and the ratio exceedsthe predetermined threshold.
 5. The vehicle noise shaping system asrecited in claim 1, wherein the tonal noise monitoring module is furtherconfigured to receive the vehicle data from one or more vehicle sensors.6. The vehicle noise shaping system as recited in claim 1, wherein thetonal noise monitoring module is further configured to select the centerfrequency of the expected tonal peak based upon the vehicle data.
 7. Thevehicle noise shaping system as recited in claim 1, wherein the vehicledata represents at least one of a speed of a vehicle, a temperatureassociated with the vehicle, and a vibration associated with thevehicle.
 8. The vehicle noise shaping system as recited in claim 1,wherein the noise shaping module is further configured to selectfiltering weights according to at least one of the difference and theratio to shape the noise cancellation signal according to the selectedfiltering weights.
 9. The vehicle noise shaping system as recited inclaim 1, wherein the weighted shaping filter comprises at least one of abandpass filter, a bandstop filter, a high-pass filter, and a low-passfilter.
 10. A system comprising: an active noise cancellation modulethat is configured to receive an environmental noise signal within avehicle cabin and to generate a noise cancellation signal based upon theenvironmental noise signal; and a tonal noise cancellation module incommunication with the active noise cancellation module, the tonal noisecancellation module including: a tonal noise monitoring module that isconfigured to: determine a center frequency of an expected tonal peakwithin a selected noise band based upon the environmental noise signal;and determine whether at least one of (1) a difference between a decibelvalue of the expected tonal peak within the selected noise band and aroot mean square value of the selected noise band and (2) a ratiobetween the decibel value of the expected tonal peak within the selectednoise band and the root mean square value of the selected noise bandexceeds a predetermined threshold; a noise shaping module that isconfigured to use a weighted shaping filter to generate the noisecancellation signal to shape the noise band when the at least one of thedifference and the ratio exceeds the predetermined threshold to shapethe noise band; and an audio output module that is configured to outputthe noise cancellation signal to smooth the expected tonal peak when theat least one of the difference and the ratio exceeds the predeterminedthreshold.
 11. The system as recited in claim 10, wherein the audiooutput module is configured to output the noise cancellation signal toone or more speakers disposed within a vehicle cabin.
 12. A methodcomprising: determining a center frequency of an expected tonal peakwithin a selected noise band based upon vehicle data; determiningwhether at least one of (1) a difference between a decibel value of theexpected tonal peak within the selected noise band and a root meansquare value of the selected noise band and (2) a ratio between thedecibel value of the expected tonal peak within the selected noise bandand the root mean square value of the selected noise band exceeds apredetermined threshold; generating a noise cancellation signal using aweighted shaping filter to shape the noise band when at least one of thedifference and the ratio exceeds the predetermined threshold; andoutputting the noise cancellation signal to smooth the expected tonalpeak when the at least one of the difference and the ratio exceeds thepredetermined threshold.
 13. The method as recited in claim 12, furthercomprising calculating at least one of the difference between thedecibel value of the expected tonal peak and the root mean square valueof the selected noise band and the ratio of the decibel value of theexpected tonal peak and the root mean square value of the selected noiseband.
 14. The method as recited in claim 12, further comprisingoutputting the noise cancellation signal to one or more speakers when atleast one of the difference and the ratio exceeds the predeterminedthreshold.
 15. The method as recited in claim 12, further comprisingreceiving the vehicle data from one or more vehicle sensors.
 16. Themethod as recited in claim 12, further comprising selecting the centerfrequency of the expected tonal peak based upon the vehicle data. 17.The method as recited in claim 12, wherein the vehicle data representsat least one of a speed of a vehicle, a temperature associated with thevehicle, and a vibration associated with the vehicle.
 18. The method asrecited in claim 12, further comprising selecting filtering weightsaccording to at least one of the difference and the ratio to shape thenoise cancellation signal according to the selected filtering weights.19. The method as recited in claim 12, wherein the weighted shapingfilter comprises at least one of a bandpass filter, a bandstop filter, ahigh-pass filter, and a low-pass filter.